Many design problems amount to an exercise in balancing multiple objectives, or what is known as a multi-objective optimization problem. For example, it is often desirable to simultaneously minimize each of a plurality of objectives, while satisfying various constraint functions. Moreover, there are often conflicts between the different objectives such that minimizing one causes another to increase in value, thereby resulting in tradeoffs between objectives. Having a design methodology that can explore tradeoffs would significantly aid fast design convergence at any abstraction level, so as to arrive at a design point that truly is the “sweet spot.”
For example, in the field of VLSI (very large scale integration) integrated circuit design, at the highest abstraction level of implementing a full chip, there is typically a tight and difficult to estimate tradeoff between power and speed. If the speed of an SRAM bitcell is increased, for example, more leakage power is typically consumed as a tradeoff. There are often several constraints on this design problem; e.g., technology capability, market forces, the design methodology, chip area, the system around the chip and design schedule. Many of these constraints could, themselves, be objectives: ideally a designer would also like to analyze the power-performance tradeoffs with chip area, the design schedule and technology costs.
Typically, designers would like to explore the tradeoff between the objectives to pick the solution that best fits their design requirements. One reason for this is that the design goals are not fully determined and an exploration of the tradeoffs is necessary to determine design capability, which in turn may be used to guide the design goals. This is often the case for SRAM bitcell design, since the bitcell is often designed during the early phases of technology development. At this time, the technology, the models and the design specifications coming from the array design are all in flux, and it is very difficult to have all requirements fixed. Knowledge of the full tradeoff between the objectives lets the designer choose a design that meets current requirements and is flexible to adapt at low cost as needs change